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Statistical Analysis of Microbiome Data with R
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Statistical Analysis of Microbiome Data with R

2018 ed.

Book Details

Format Hardback or Cased Book
ISBN-10 9811315337
ISBN-13 9789811315336
Edition 2018 ed.
Publisher Springer Verlag, Singapore
Imprint Springer Verlag, Singapore
Country of Manufacture SG
Country of Publication GB
Publication Date Oct 20th, 2018
Print length 505 Pages
Weight 930 grams
Dimensions 16.40 x 24.30 x 3.20 cms
Ksh 25,200.00
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This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors'' research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research.

The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.


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